Dynamic Credit Default Swaps Curves in a Network Topology

Abstract

The issues of default spillover and systemic risk should be weighted for the market participants with longer credit exposures, and for regulators with a mission to stabilize financial markets. The US banks contribute more to the long-run default spillover before 2012, whereas the European banks are major default transmitters during and after the European debt crisis either in the long-run or short-run. The outperformance of the network DNS model indicates that the prediction on CDS curve requires network information.JEL classification: C32, C51, G17

Tail event driven networks of SIFIs

“…The likelihood of simultaneous slumps in the banking industry is potentially greater than that they boom together, which is a typical feature under systemic risk. Diebold and Yılmaz (2014) and Xu et al (2016) find an increased total interconnectedness during the crisis period, resulting in more fragile financial markets evidence by high comovement, contagion and spillover. By investigating global banking sectors, Dungey and Gajurel (2015) find a systematic contagion, defined as the potential increased exposure of banks to total systemic risk, rises in a crisis.…”

Data science and digital society

“…The flow of risk emitters and receivers is given above in Figure 1. One sees the dominant US risk emitting banking sector, Xiu et al (2017) Dynamic Topic Modeling. DTM is a text mining tool that uses a bag of words model for the flow of topics over time.…”